Abstract
Clarifying the impact mechanisms of landscape patterns on ecosystem services is highly important for effective ecosystem protection, policymaking, and landscape planning. However, previous literature lacks knowledge about the impact mechanisms of landscape patterns on ecosystem services from a spatial perspective. Thus, this study measured landscape patterns and the ecosystem services value (ESV) using a series of landscape pattern metrics and an improved benefit transfer method based on land-use data from 2015. It explores the impact mechanisms of the landscape pattern metrics on the ESV using the ordinary least-squares method and spatial regression models in the middle reaches of the Yangtze River Urban Agglomerations (MRYRUA), China. We found that forestland was the main landscape type in the MRYRUA, followed by cultivated land, and the fragmentation degree of cultivated land was significantly higher than that of forestland. The findings demonstrate that landscape pattern metrics had a significant impact on ecosystem services, but could vary greatly. Moreover, ecosystem services in the MRYRUA exhibited significant spatial spillover effects and cross-regional collaborative governance was an effective means of landscape planning. This paper acts as a scientific reference and effective guidance for landscape planning and regional ecosystem conservation in MRYRUA and other similarly fast-growing urban agglomerations.
Original language | English (US) |
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Article number | 5063 |
Pages (from-to) | 1-26 |
Number of pages | 26 |
Journal | International journal of environmental research and public health |
Volume | 17 |
Issue number | 14 |
DOIs | |
State | Published - Jul 2 2020 |
Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Public Health, Environmental and Occupational Health
- Pollution
- Health, Toxicology and Mutagenesis
Keywords
- China
- Ecosystem services value
- Landscape pattern metrics
- Middle reaches of the Yangtze River Urban Agglomerations
- Spatial regression analysis